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Record W2481721784 · doi:10.1017/ccol0521770440.008

Laughing at "others"

2001· book-chapter· en· W2481721784 on OpenAlexaff
Edward W. Berry

Bibliographic record

VenueCambridge University Press eBooks · 2001
Typebook-chapter
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLaughterComedyCarnivalesqueComicsFeelingJokeLiteratureAestheticsArtPsychologySocial psychology

Abstract

fetched live from OpenAlex

As a dramatic form, comedy can exist without laughter, but most of the plays that we consider comedies are engines of laughter, and one of the great pleasures of comic theatre is the feeling of exhilaration and release that laughter provides. Despite much theorizing, the causes of laughter and its significance in human life remain a mystery. The impulse to laugh, for one thing, is deeply equivocal. At times, as when we laugh “with” someone, laughter may be a mechanism by which we identify with another human being, a means of psychological and social bonding. At other times, as when we laugh “at” someone, the same physical reaction may be a form of aggressive self-assertion. The former kind of laughter, in which human and societal divisions are dissolved in communal merriment, we might call, loosely following Bakhtin, carnivalesque. The latter, in which such divisions are perversely reinforced, we might call Hobbesian, after Thomas Hobbes, who defined laughter as an expression of superiority, a feeling of “sudden glory arising from some sudden conception of some eminency in ourselves, by comparison with the infirmity of others.” Both kinds of laughter, curiously, can strengthen certain kinds of social communion: the carnivalesque, by casting wide the net of community, implying that we are all, at some level, one; the Hobbesian, by affirming the superiority of one community in opposition to an individual or group outside it. Romantic and Saturnalian comedy tend towards carnivalesque laughter; satiric comedy, towards Hobbesian.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.251
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2001
Admission routes1
Has abstractyes

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